Protein folding: defining a "standard" set of experimental conditions and a preliminary kinetic data set of two-state proteins

The Critical Role of the Variable Domain in Driving Proteotoxicity and Aggregation in Full-length Light Chains

Light chain (AL) amyloidosis is the most common systemic amyloid disease characterized by abnormal accumulation of amyloid fibrils derived from immunoglobulin light chains (LCs). Both full-length (FL) LCs and their isolated variable (VL) and constant (CL) domains contribute to amyloid deposits in multiple organs, with the VL domain predominantly forming the fibril core. However, the role and interplay of these domains in amyloid aggregation and toxicity are poorly understood. Characterizing the amyloidogenic λ6-LC AL55, this study explores the properties of both FL and isolated domains and compares them with the available patient-derived data. FL AL55 biophysical features result from the interplay between its VL and CL domains where the limited VL-CL interface might play a major role. Slow refolding kinetic of FL confirms the unfolded VL domain as a kinetic trap possibly shifting the process towards misfolding. The X-ray structure of FL AL55 shows that VL domains may detach from the native dimeric assembly and establish non-native interdimeric interfaces. Additionally, isolated VL domains display significantly lower soluble toxicity compared to FL and do not form fibrils similar to those found ex vivo. Thus the data obtained in this work allowed us to draw a molecular sketch of the aggregation pathway for amyloidogenic LCs.

Quantifying protein unfolding kinetics with a high-throughput microfluidic platform

Even after folding, proteins transiently sample unfolded or partially unfolded intermediates, and these species are often at risk of irreversible alteration (e.g. via proteolysis, aggregation, or post-translational modification). Kinetic stability, in addition to thermodynamic stability, can directly impact protein lifetime, abundance, and the formation of alternative, sometimes disruptive states. However, we have very few measurements of protein unfolding rates or how mutations alter these rates, largely due to technical challenges associated with their measurement. To address this need, we developed SPARKfold (Simultaneous Proteolysis Assay Revealing Kinetics of Folding), a microfluidic platform to express, purify, and measure unfolding rate constants for >1000 protein variants in parallel via on-chip native proteolysis. To demonstrate the power and potential of SPARKfold, we determined unfolding rate constants for 1,104 protein samples in parallel. We built a library of 31 dihydrofolate reductase (DHFR) orthologs with up to 78 chamber replicates per variant to provide the statistical power required to evaluate the system's ability to resolve subtle effects. SPARKfold rate constants for 5 constructs agreed with those obtained using traditional techniques across a 150-fold range, validating the accuracy of the technique. Comparisons of mutant kinetic effects via SPARKfold with previously published measurements impacts on folding thermodynamics provided information about the folding transition state and pathways via φ analysis. Overall, SPARKfold enables rapid characterization of protein variants to dissect the nature of the unfolding transition state. In future work, SPARKfold can reveal mutations that drive misfolding and aggregation and enable rational design of kinetically hyperstable variants for industrial use in harsh environments.

Predicting absolute protein folding stability using generative models

While there has been substantial progress in our ability to predict changes in protein stability due to amino acid substitutions, progress has been slower in methods to predict the absolute stability of a protein. Here, we show how a generative model for protein sequence can be leveraged to predict absolute protein stability. We benchmark our predictions across a broad set of proteins and find a mean error of 1.5 kcal/mol and a correlation coefficient of 0.7 for the absolute stability across a range of natural, small- to medium-sized proteins up to ca. 150 amino acid residues. We analyze current limitations and future directions including how such a model may be useful for predicting conformational free energies. Our approach is simple to use and freely available at an online implementation available via https://github.com/KULL-Centre/_2024_cagiada_stability.

PRKN-linked familial Parkinson's disease: cellular and molecular mechanisms of disease-linked variants

Parkinson's disease (PD) is a common and incurable neurodegenerative disorder that arises from the loss of dopaminergic neurons in the substantia nigra and is mainly characterized by progressive loss of motor function. Monogenic familial PD is associated with highly penetrant variants in specific genes, notably the PRKN gene, where homozygous or compound heterozygous loss-of-function variants predominate. PRKN encodes Parkin, an E3 ubiquitin-protein ligase important for protein ubiquitination and mitophagy of damaged mitochondria. Accordingly, Parkin plays a central role in mitochondrial quality control but is itself also subject to a strict protein quality control system that rapidly eliminates certain disease-linked Parkin variants. Here, we summarize the cellular and molecular functions of Parkin, highlighting the various mechanisms by which PRKN gene variants result in loss-of-function. We emphasize the importance of high-throughput assays and computational tools for the clinical classification of PRKN gene variants and how detailed insights into the pathogenic mechanisms of PRKN gene variants may impact the development of personalized therapeutics.

On the Chemistry of Aqueous Ammonium Acetate Droplets during Native Electrospray Ionization Mass Spectrometry

Ammonium acetate (NH4Ac) is a widely used solvent additive in native electrospray ionization (ESI) mass spectrometry. NH4Ac can undergo proton transfer to form ammonia and acetic acid (NH4+ + Ac- → NH3 + HAc). The volatility of these products ensures that electrosprayed ions are free of undesired adducts. NH4Ac dissolution in water yields pH 7, providing "physiological" conditions. However, NH4Ac is not a buffer at pH 7 because NH4+ and Ac- are not a conjugate acid/base pair (Konermann, L. J. Am. Soc. Mass Spectrom. 2017, 28, 1827-1835.). In native ESI, it is desirable that analytes experience physiological conditions not only in bulk solution but also while they reside in ESI droplets. Little is known about the internal milieu of NH4Ac-containing ESI droplets. The current work explored the acid/base chemistry of such droplets, starting from a pH 7 analyte solution. We used a two-pronged approach involving evaporation experiments on bulk solutions under ESI-mimicking conditions, as well as molecular dynamics simulations using a newly developed algorithm that allows for proton transfer. Our results reveal that during droplet formation at the tip of the Taylor cone, electrolytically generated protons get neutralized by Ac-, making NH4+ the net charge carriers in the weakly acidic nascent droplets. During the subsequent evaporation, the droplets lose water as well as NH3 and HAc that were generated by proton transfer. NH3 departs more quickly because of its greater volatility, causing the accumulation of HAc. Together with residual Ac-, these HAc molecules form an acetate buffer that stabilizes the average droplet pH at 5.4 ± 0.1, as governed by the Henderson-Hasselbalch equation. The remarkable success of native ESI investigations in the literature implies that this pH drop by ∼1.6 units relative to the initially neutral analyte solution can be tolerated by most biomolecular analytes on the short time scale of the ESI process.

Pathfinder: Protein folding pathway prediction based on conformational sampling

The study of protein folding mechanism is a challenge in molecular biology, which is of great significance for revealing the movement rules of biological macromolecules, understanding the pathogenic mechanism of folding diseases, and designing protein engineering materials. Based on the hypothesis that the conformational sampling trajectory contain the information of folding pathway, we propose a protein folding pathway prediction algorithm named Pathfinder. Firstly, Pathfinder performs large-scale sampling of the conformational space and clusters the decoys obtained in the sampling. The heterogeneous conformations obtained by clustering are named seed states. Then, a resampling algorithm that is not constrained by the local energy basin is designed to obtain the transition probabilities of seed states. Finally, protein folding pathways are inferred from the maximum transition probabilities of seed states. The proposed Pathfinder is tested on our developed test set (34 proteins). For 11 widely studied proteins, we correctly predicted their folding pathways and specifically analyzed 5 of them. For 13 proteins, we predicted their folding pathways to be further verified by biological experiments. For 6 proteins, we analyzed the reasons for the low prediction accuracy. For the other 4 proteins without biological experiment results, potential folding pathways were predicted to provide new insights into protein folding mechanism. The results reveal that structural analogs may have different folding pathways to express different biological functions, homologous proteins may contain common folding pathways, and α-helices may be more prone to early protein folding than β-strands.

Functional advantages of building nanosystems using multiple molecular components

Over half of all the natural nanomachines in living organisms are multimeric and likely exploit the self-assembly of their components to provide functional benefits. However, the advantages and disadvantages of building nanosystems using multiple molecular components remain relatively unexplored at the thermodynamic, kinetic and functional levels. In this study we used theory and a simple DNA-based model that forms the same nanostructures with different numbers of components to advance our knowledge in this area. Despite its lower assembly rate, we found that a system built with three components may undergo a more cooperative assembly transition from less preorganized components, which facilitates the emergence of functionalities. Using simple variations of its components, we also found that trimeric nanosystems display a much higher level of programmability than their dimeric counterparts because they can assemble with various levels of cooperativity, self-inhibition and time-dependent properties. We show here how two simple strategies (for example, cutting and adding components) can be employed to efficiently programme the regulatory function of a more complex, artificially selected, RNA-cleaving catalytic nanosystem.

Volumetric Properties of the Transition State Ensemble for Protein Folding

Understanding how high hydrostatic pressure affects biomacromolecular interaction is important for deciphering the molecular mechanisms by which organisms adapt to live at the bottom of the ocean. The relative effect of hydrostatic pressure on the rates of folding/unfolding reactions is defined by the volumetric properties of the transition state ensemble relative to the folded and unfolded states. All-atom structure-based molecular dynamics simulations combined with quantitative computational protocol to compute volumes from three-dimensional coordinates allow volumetric mapping of protein folding landscape. This, is turn, provides qualitative understanding of the effects of hydrostatic pressure on energy landscape of proteins. The computational results for six different proteins are directly benchmark against experimental data and show an excellent agreement. Both experiments and computation show that the transition-state ensemble volume appears to be in-between the folded and unfolded state volumes, and thus the hydrostatic pressure accelerates protein unfolding.

Disease-linked mutations cause exposure of a protein quality control degron

More than half of disease-causing missense variants are thought to lead to protein degradation, but the molecular mechanism of how these variants are recognized by the cell remains enigmatic. Degrons are stretches of amino acids that help mediate recognition by E3 ligases and thus confer protein degradation via the ubiquitin-proteasome system. While degrons that mediate controlled degradation of, for example, signaling components and cell-cycle regulators are well described, so-called protein-quality-control degrons that mediate the degradation of destabilized proteins are poorly understood. Here, we show that disease-linked dihydrofolate reductase (DHFR) missense variants are structurally destabilized and chaperone-dependent proteasome targets. We find two regions in DHFR that act as degrons, and the proteasomal turnover of one of these was dependent on the molecular chaperone Hsp70. Structural analyses by nuclear magnetic resonance (NMR) and hydrogen/deuterium exchange revealed that this degron is buried in wild-type DHFR but becomes transiently exposed in the disease-linked missense variants.

Kinetic model of GPCR-G protein interactions reveals allokairic modulation of signaling

Established models of ternary complex formation between hormone, G protein coupled receptor (GPCR), and G protein assume that all interactions occur under equilibrium conditions. However, recent studies have established that the lifetimes of these interactions are comparable to the duration of hormone activated GPCR signaling. To simulate interactions during such non-equilibrium conditions, we propose a kinetic model wherein the receptor undergoes rate-limiting transitions between two hormone-bound active states. Simulations, using experimentally measured parameters, demonstrate transient states in ternary complex formation, and delineate the phenomenon of GPCR priming, wherein non-cognate G proteins substantially enhance cognate G protein signaling. Our model reveals that kinetic barriers of slow receptor interconversion can be overcome through allokairic modulation, a regulatory mechanism of ternary complex formation and downstream signaling.

Experimentally validated kinetic simulations uncover transient enhancement of GPCR ternary complex formation by allokairic effectors.

Lessons from a quarter century of being human in protein science

Over the past quarter century, my engagement with the protein society has allowed me to witness first-hand the evolution of our deepening understanding of the complexity of protein folding landscapes. During my own evolution as a protein scientist, my passion for protein folding has deepened into an obsession with mapping and decoding the thermodynamic and kinetic secrets of protein landscapes - especially those of rebel proteins, whose "non-traditional" behavior has challenged our paradigms and inspired the expansion of our models and methods. It is perhaps not surprising that I see parallels in the evolution of the landscape framework and in the development of our own trajectories as humans in STEM. Just as with proteins however, we need to recognize that our individual human landscapes are not isolated from our local departmental and institutional communities, and are integrated into the larger networks of our STEM disciplines, academia, industry and/or government, not to mention society. My experience with hundreds of participants in the Being Human in STEM initiative that Amherst College undergraduates and I co-founded in 2016 has helped me find hope for STEM and humanity. If we commit to reconciling our identities as scientists with our responsibilities as human beings, together we can accelerate the evolution of individual, community and societal landscapes to contribute to addressing the dire challenges facing our planet. This article is protected by copyright. All rights reserved.

A thermodynamic atlas of proteomes reveals energetic innovation across the tree of life

Protein stability is a fundamental molecular property enabling organisms to adapt to their biological niches. How this is facilitated and whether there are kingdom specific or more general universal strategies is not known. A principal obstacle to addressing this issue is that the vast majority of proteins lack annotation, specifically thermodynamic annotation, beyond the amino acid and chromosome information derived from genome sequencing. To address this gap and facilitate future investigation into large-scale patterns of protein stability and dynamics within and between organisms, we applied a unique ensemble-based thermodynamic characterization of protein folds to a substantial portion of extant sequenced genomes. Using this approach, we compiled a database resource focused on the position-specific variation in protein stability. Interrogation of the database reveals; 1) domains of life exhibit distinguishing thermodynamic features, with eukaryotes particularly different from both archaea and bacteria, 2) the optimal growth temperature of an organism is proportional to the average apolar enthalpy of its proteome, 3) intrinsic disorder content is also proportional to the apolar enthalpy (but unexpectedly not the predicted stability at 25 °C), and 4) secondary structure and global stability information of individual proteins is extractable. We hypothesize that wider access to residue-specific thermodynamic information of proteomes will result in deeper understanding of mechanisms driving functional adaptation and protein evolution. Our database is free for download at https://afc-science.github.io/thermo-env-atlas/.

Prediction of Folding and Unfolding Rates of Proteins with Simple Models

Large differences exist between the experimentally measured folding and unfolding rates in single-domain proteins, which range from seconds to microseconds. Considerable effort has been dedicated to develop methods for the prediction of these rates using a simple set of rules. Much of this work has focused in identifying structural metrics derived from experimentally resolved protein structures that serve as good predictors of folding rates. An alternative to this ad-hoc methodology is the use of phenomenological free energy models, parametrized with empirical parameters. This alternative approach has become very useful to obtain estimates of folding and, importantly, also unfolding rates with only the information of protein size and secondary structure. Here we present the fundamentals of this type of approach and introduce a recent implementation of this predictive method.

Mechanism of Thermal Protein Aggregation: Experiments and Molecular Dynamics Simulations on the High-Temperature Behavior of Myoglobin

Proteins that encounter unfavorable solvent conditions are prone to aggregation, a phenomenon that remains poorly understood. This work focuses on myoglobin (Mb) as a model protein. Upon heating, Mb produces amorphous aggregates. Thermal unfolding experiments at low concentration (where aggregation is negligible), along with centrifugation assays, imply that Mb aggregation proceeds via globally unfolded conformers. This contrasts studies on other proteins that emphasized the role of partially folded structures as aggregate precursors. Molecular dynamics (MD) simulations were performed to gain insights into the mechanism by which heat-unfolded Mb molecules associate with one another. A prerequisite for these simulations was the development of a method for generating monomeric starting structures. Periodic boundary condition artifacts necessitated the implementation of a partially immobilized water layer lining the walls of the simulation box. Aggregation simulations were performed at 370 K to track the assembly of monomeric Mb into pentameric species. Binding events were preceded by multiple unsuccessful encounters. Even after association, protein-protein contacts remained in flux. Binding was mediated by hydrophobic contacts, along with salt bridges that involved hydrophobically embedded Lys residues. Overall, this work illustrates that atomistic MD simulations are well suited for garnering insights into protein aggregation mechanisms.

Protein Folding Dynamics as Diffusion on a Free Energy Surface: Rate Equation Terms, Transition Paths, and Analysis of Single-Molecule Photon Trajectories

The rates of protein (un)folding are often described as diffusion on the projection of a hyperdimensional energy landscape onto a few (ideally one) order parameters. Testing such an approximation by experiment requires resolving the reactive transition paths of individual molecules, which is now becoming feasible with advanced single-molecule spectroscopic techniques. This has also sparked the interest of theorists in better understanding reactive transition paths. Here we focus on these issues aiming to establish (i) practical guidelines for the mechanistic interpretation of transition path times (TPT) and (ii) methods to extract the free energy surface and protein dynamics from the maximum likelihood analysis of photon trajectories (MLA-PT). We represent the (un)folding rates as diffusion on a 1D free energy surface with the FRET efficiency as a reaction coordinate proxy. We then perform diffusive kinetic simulations on surfaces with two minima and a barrier, but with different shapes (curvatures, barrier height, and symmetry), coupled to stochastic simulations of photon emissions that reproduce current SM-FRET experiments. From the analysis of transition paths, we find that the TPT is inversely proportional to the barrier height (difference in free energy between minimum and barrier top) for any given surface shape, and that dividing the TPT into climb and descent segments provides key information about the barrier's symmetry. We also find that the original MLA-PT procedure used to determine the TPT from experiments underestimates its value, particularly for the cases with smaller barriers (e.g., fast folders), and we suggest a simple strategy to correct for this bias. Importantly, we also demonstrate that photon trajectories contain enough information to extract the 1D free energy surface's shape and dynamics (if TPT is >4-5-fold longer than the interphoton time) using the MLA-PT directly implemented with a diffusive free energy surface model. When dealing with real (unknown) experimental data, the comparison between the likelihoods of the free energy surface and discrete kinetic three-state models can be used to evaluate the statistical significance of the estimated free energy surface.

Topological principles of protein folding

What is the topology of a protein and what governs protein folding to a specific topology? This is a fundamental question in biology. The protein folding reaction is a critically important cellular process, which is failing in many prevalent diseases. Understanding protein folding is also key to the design of new proteins for applications. However, our ability to predict the folding of a protein chain is quite limited and much is still unknown about the topological principles of folding. Current predictors of folding kinetics, including the contact order and size, present a limited predictive power, suggesting that these models are fundamentally incomplete. Here, we use a newly developed mathematical framework to define and extract the topology of a native protein conformation beyond knot theory, and investigate the relationship between native topology and folding kinetics in experimentally characterized proteins. We show that not only the folding rate, but also the mechanistic insight into folding mechanisms can be inferred from topological parameters. We identify basic topological features that speed up or slow down the folding process. The approach enabled the decomposition of protein 3D conformation into topologically independent elementary folding units, called circuits. The number of circuits correlates significantly with the folding rate, offering not only an efficient kinetic predictor, but also a tool for a deeper understanding of theoretical folding models. This study contributes to recent work that reveals the critical relevance of topology to protein folding with a new, contact-based, mathematically rigorous perspective. We show that topology can predict folding kinetics when geometry-based predictors like contact order and size fail.

Nonrefoldability is Pervasive Across the E. coli Proteome

Decades of research on protein folding have primarily focused on a subset of small proteins that can reversibly refold from a denatured state. However, these studies have generally not been representative of the complexity of natural proteomes, which consist of many proteins with complex architectures and domain organizations. Here, we introduce an experimental approach to probe protein refolding kinetics for whole proteomes using mass spectrometry-based proteomics. Our study covers the majority of the soluble E. coli proteome expressed during log-phase growth, and among this group, we find that one-third of the E. coli proteome is not intrinsically refoldable on physiological time scales, a cohort that is enriched with certain fold-types, domain organizations, and other biophysical features. We also identify several properties and fold-types that are correlated with slow refolding on the minute time scale. Hence, these results illuminate when exogenous factors and processes, such as chaperones or cotranslational folding, might be required for efficient protein folding.

Linking thermodynamics and measurements of protein stability

We review the background, theory and general equations for the analysis of equilibrium protein unfolding experiments, focusing on denaturant and heat-induced unfolding. The primary focus is on the thermodynamics of reversible folding/unfolding transitions and the experimental methods that are available for extracting thermodynamic parameters. We highlight the importance of modelling both how the folding equilibrium depends on a perturbing variable such as temperature or denaturant concentration, and the importance of modelling the baselines in the experimental observables.

The change of conditions does not affect Ros87 downhill folding mechanism

Downhill folding has been defined as a unique thermodynamic process involving a conformations ensemble that progressively loses structure with the decrease of protein stability. Downhill folders are estimated to be rather rare in nature as they miss an energetically substantial folding barrier that can protect against aggregation and proteolysis. We have previously demonstrated that the prokaryotic zinc finger protein Ros87 shows a bipartite folding/unfolding process in which a metal binding intermediate converts to the native structure through a delicate barrier-less downhill transition. Significant variation in folding scenarios can be detected within protein families with high sequence identity and very similar folds and for the same sequence by varying conditions. For this reason, we here show, by means of DSC, CD and NMR, that also in different pH and ionic strength conditions Ros87 retains its partly downhill folding scenario demonstrating that, at least in metallo-proteins, the downhill mechanism can be found under a much wider range of conditions and coupled to other different transitions. We also show that mutations of Ros87 zinc coordination sphere produces a different folding scenario demonstrating that the organization of the metal ion core is determinant in the folding process of this family of proteins.

Global analysis of protein stability by temperature and chemical denaturation

The stability of a protein is a fundamental property that determines under which conditions, the protein is functional. Equilibrium unfolding with denaturants requires preparation of several samples and only provides the free energy of folding when performed at a single temperature. The typical sample requirement is around 0.5-1 mg of protein. If the stability of many proteins or protein variants needs to be determined, substantial protein production may be needed. Here we have determined the stability of acyl-coenzyme A binding protein at pH 5.3 and chymotrypsin inhibitor 2 at pH 3 and pH 6.25 by combined temperature and denaturant unfolding. We used a setup where tryptophan fluorescence is measured in quartz capillaries where only 10 μl is needed. Temperature unfolding of a series of 15 samples at increasing denaturant concentrations provided accurate and precise thermodynamic parameters. We find that the number of samples may be further reduced and less than 10 μg of protein in total are needed for reliable stability measurements. For assessment of stability of protein purified in small scale e.g. in micro plate format, our method will be highly applicable. The routine for fitting the experimental data is made available as a python notebook.

Folding of copper proteins: role of the metal?

Copper is a redox-active transition metal ion required for the function of many essential human proteins. For biosynthesis of proteins coordinating copper, the metal may bind before, during or after folding of the polypeptide. If the metal binds to unfolded or partially folded structures of the protein, such coordination may modulate the folding reaction. The molecular understanding of how copper is incorporated into proteins requires descriptions of chemical, thermodynamic, kinetic and structural parameters involved in the formation of protein-metal complexes. Because free copper ions are toxic, living systems have elaborate copper-transport systems that include particular proteins that facilitate efficient and specific delivery of copper ions to target proteins. Therefore, these pathways become an integral part of copper protein folding in vivo. This review summarizes biophysical-molecular in vitro work assessing the role of copper in folding and stability of copper-binding proteins as well as protein-protein copper exchange reactions between human copper transport proteins. We also describe some recent findings about the participation of copper ions and copper proteins in protein misfolding and aggregation reactions in vitro.

Biophysical and Mechanistic Models for Disease-Causing Protein Variants

The rapid decrease in DNA sequencing cost is revolutionizing medicine and science. In medicine, genome sequencing has revealed millions of missense variants that change protein sequences, yet we only understand the molecular and phenotypic consequences of a small fraction. Within protein science, high-throughput deep mutational scanning experiments enable us to probe thousands of variants in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense variants in proteins. We focus on the role of changes in protein stability as a driver for disease, and how experiments, biophysical models, and computation are providing a framework for understanding and predicting how changes in protein sequence affect cellular protein stability.

PyFolding: Open-Source Graphing, Simulation, and Analysis of the Biophysical Properties of Proteins

For many years, curve-fitting software has been heavily utilized to fit simple models to various types of biophysical data. Although such software packages are easy to use for simple functions, they are often expensive and present substantial impediments to applying more complex models or for the analysis of large data sets. One field that is reliant on such data analysis is the thermodynamics and kinetics of protein folding. Over the past decade, increasingly sophisticated analytical models have been generated, but without simple tools to enable routine analysis. Consequently, users have needed to generate their own tools or otherwise find willing collaborators. Here we present PyFolding, a free, open-source, and extensible Python framework for graphing, analysis, and simulation of the biophysical properties of proteins. To demonstrate the utility of PyFolding, we have used it to analyze and model experimental protein folding and thermodynamic data. Examples include: 1) multiphase kinetic folding fitted to linked equations, 2) global fitting of multiple data sets, and 3) analysis of repeat protein thermodynamics with Ising model variants. Moreover, we demonstrate how PyFolding is easily extensible to novel functionality beyond applications in protein folding via the addition of new models. Example scripts to perform these and other operations are supplied with the software, and we encourage users to contribute notebooks and models to create a community resource. Finally, we show that PyFolding can be used in conjunction with Jupyter notebooks as an easy way to share methods and analysis for publication and among research teams.

PFDB: A standardized protein folding database with temperature correction

We constructed a standardized protein folding kinetics database (PFDB) in which the logarithmic rate constants of all listed proteins are calculated at the standard temperature (25 °C). A temperature correction based on the Eyring–Kramers equation was introduced for proteins whose folding kinetics were originally measured at temperatures other than 25 °C. We verified the temperature correction by comparing the logarithmic rate constants predicted and experimentally observed at 25 °C for 14 different proteins, and the results demonstrated improvement of the quality of the database. PFDB consists of 141 (89 two-state and 52 non-two-state) single-domain globular proteins, which has the largest number among the currently available databases of protein folding kinetics. PFDB is thus intended to be used as a standard for developing and testing future predictive and theoretical studies of protein folding. PFDB can be accessed from the following link: http://lee.kias.re.kr/~bala/PFDB.

Protein stability and degradation in health and disease

The cellular proteome performs highly varied functions to sustain life. Since most of these functions require proteins to fold properly, they can be impaired by mutations that affect protein structure, leading to diseases such as Alzheimer's disease, cystic fibrosis, and Lynch syndrome. The cell has evolved an intricate protein quality control (PQC) system that includes degradation pathways and a multitude of molecular chaperones and co-chaperones, all working together to catalyze the refolding or removal of aberrant proteins. Thus, the PQC system limits the harmful consequences of dysfunctional proteins, including those arising from disease-causing mutations. This complex system is still not fully understood. In particular the structural and sequence motifs that, when exposed, trigger degradation of misfolded proteins are currently under investigation. Moreover, several attempts are being made to activate or inhibit parts of the PQC system as a treatment for diseases. Here, we briefly review the present knowledge on the PQC system and list current strategies that are employed to exploit the system in disease treatment.

An Overlapping Region between the Two Terminal Folding Units of the Outer Surface Protein A (OspA) Controls Its Folding Behavior

Although many naturally occurring proteins consist of multiple domains, most studies on protein folding to date deal with single-domain proteins or isolated domains of multi-domain proteins. Studies of multi-domain protein folding are required for further advancing our understanding of protein folding mechanisms. Borrelia outer surface protein A (OspA) is a β-rich two-domain protein, in which two globular domains are connected by a rigid and stable single-layer β-sheet. Thus, OspA is particularly suited as a model system for studying the interplays of domains in protein folding. Here, we studied the equilibria and kinetics of the urea-induced folding-unfolding reactions of OspA probed with tryptophan fluorescence and ultraviolet circular dichroism. Global analysis of the experimental data revealed compelling lines of evidence for accumulation of an on-pathway intermediate during kinetic refolding and for the identity between the kinetic intermediate and a previously described equilibrium unfolding intermediate. The results suggest that the intermediate has the fully native structure in the N-terminal domain and the single layer β-sheet, with the C-terminal domain still unfolded. The observation of the productive on-pathway folding intermediate clearly indicates substantial interactions between the two domains mediated by the single-layer β-sheet. We propose that a rigid and stable intervening region between two domains creates an overlap between two folding units and can energetically couple their folding reactions.

Estimating the mean first passage time of protein misfolding

Most theoretical and experimental studies confirm that proteins fold in the time scale of microseconds to milliseconds, but the kinetics of the protein misfolding remains largely unexplored. The kinetics of unfolding-folding-misfolding equilibrium in proteins is formulated in the analytical framework of the Master equation. The folded, unfolded and the misfolded state are characterized in terms of their respective contacts. The Mean First Passage Time (MFPT) to acquire the misfolded conformation from the native or folded state is derived from this equation with different boundary conditions. The MFPT is found to be practically independent of the length of the protein, the number of native contacts and the rate constant for the misfolded to the folded state. The results obtained from the survival probability are directly correlated to the age of onset and appearance of misfolding diseases in humans.

drFrnE Represents a Hitherto Unknown Class of Eubacterial Cytoplasmic Disulfide Oxido-Reductases

AIMS

Living cells employ thioredoxin and glutaredoxin disulfide oxido-reductases to protect thiol groups in intracellular proteins. FrnE protein of Deinococcus radiodurans (drFrnE) is a disulfide oxido-reductase that is induced in response to Cd²⁺ exposure and is involved in cadmium and radiation tolerance. The aim of this study is to probe structure, function, and cellular localization of FrnE class of proteins.

RESULTS

Here, we show drFrnE as a novel cytoplasmic oxido-reductase that could be functional in eubacteria under conditions where thioredoxin/glutaredoxin systems are inhibited or absent. Crystal structure analysis of drFrnE reveals thioredoxin fold with an alpha helical insertion domain and a unique, flexible, and functionally important C-terminal tail. The C-tail harbors a novel 239-CX₄C-244 motif that interacts with the active site 22-CXXC-25 motif. Crystal structures with different active site redox states, including mixed disulfide (Cys22-Cys244), are reported here. The biochemical data show that 239-CX₄C-244 motif channels electrons to the active site cysteines. drFrnE is more stable in the oxidized form, compared with the reduced form, supporting its role as a disulfide reductase. Using bioinformatics analysis and fluorescence microscopy, we show cytoplasmic localization of drFrnE. We have found "true" orthologs of drFrnE in several eubacterial phyla and, interestingly, all these groups apparently lack a functional glutaredoxin system. Innovation and Conclusion: We show that drFrnE represents a new class of hitherto unknown intracellular oxido-reductases that are abundantly present in eubacteria. Unlike other well-known oxido-reductases, FrnE harbors an additional dithiol motif that acts as a conduit to channel electrons to the active site during catalytic turnover. Antioxid. Redox Signal. 28, 296-310.

Denaturant-specific effects on the structural energetics of a protein-denatured ensemble

Protein thermodynamic stability is intricately linked to cellular function, and altered stability can lead to dysfunction and disease. The linear extrapolation model (LEM) is commonly used to obtain protein unfolding free energies ([Formula: see text]) by extrapolation of solvent denaturation data to zero denaturant concentration. However, for some proteins, different denaturants result in non-coincident LEM-derived [Formula: see text] values, raising questions about the inherent assumption that the obtained [Formula: see text] values are intrinsic to the protein. Here, we used single-molecule FRET measurements to better understand such discrepancies by directly probing changes in the dimensions of the protein G B1 domain (GB1), a well-studied protein folding model, upon urea and guanidine hydrochloride denaturation. A comparison of the results for the two denaturants suggests denaturant-specific structural energetics in the GB1 denatured ensemble, revealing a role of the denatured state in the variable thermodynamic behavior of proteins.

Rules for connectivity of secondary structure elements in protein: Two-layer αβ sandwiches

In protein structures, the fold is described according to the spatial arrangement of secondary structure elements (SSEs: α-helices and β-strands) and their connectivity. The connectivity or the pattern of links among SSEs is one of the most important factors for understanding the variety of protein folds. In this study, we introduced the connectivity strings that encode the connectivities by using the types, positions, and connections of SSEs, and computationally enumerated all the connectivities of two-layer αβ sandwiches. The calculated connectivities were compared with those in natural proteins determined using MICAN, a nonsequential structure comparison method. For 2α-4β, among 23,000 of all connectivities, only 48 were free from irregular connectivities such as loop crossing. Of these, only 20 were found in natural proteins and the superfamilies were biased toward certain types of connectivities. A similar disproportional distribution was confirmed for most of other spatial arrangements of SSEs in the two-layer αβ sandwiches. We found two connectivity rules that explain the bias well: the abundances of interlayer connecting loops that bridge SSEs in the distinct layers; and nonlocal β-strand pairs, two spatially adjacent β-strands located at discontinuous positions in the amino acid sequence. A two-dimensional plot of these two properties indicated that the two connectivity rules are not independent, which may be interpreted as a rule for the cooperativity of proteins.

The dock-and-coalesce mechanism for the association of a WASP disordered region with the Cdc42 GTPase

Intrinsically disordered proteins (IDPs) play key roles in signaling and regulation. Many IDPs undergo folding upon binding to their targets. We have proposed that coupled folding and binding of IDPs generally follow a dock-and-coalesce mechanism, whereby a segment of the IDP, through diffusion, docks to its cognate subsite and, subsequently, the remaining segments coalesce around their subsites. Here, by a combination of experiment and computation, we determined the precise form of dock-and-coalesce operating in the association between the intrinsically disordered GTPase-binding domain (GBD) of the Wiskott-Aldrich Syndrome protein and the Cdc42 GTPase. The association rate constants (k_a ) were measured by stopped-flow fluorescence under various solvent conditions. k_a reached 10⁷ m^-1 ·s^-1 at physiological ionic strength and had a strong salt dependence, suggesting that an electrostatically enhanced, diffusion-controlled docking step may be rate limiting. Our computation, based on the transient-complex theory, identified the N-terminal basic region of the GBD as the docking segment. However, several other changes in solvent conditions provided strong evidence that the coalescing step also contributed to determining the magnitude of k_a . Addition of glucose and trifluoroethanol and an increase in temperature all produced experimental k_a values much higher than expected from the effects on the docking rate alone. Conversely, addition of urea led to k_a values much lower than expected if only the docking rate was affected. These results all pointed to k_a being approximately two-thirds of the docking rate constant under physiological solvent conditions.

Using Cooperatively Folded Peptides To Measure Interaction Energies and Conformational Propensities

The rates and equilibria of the folding of biopolymers are determined by the conformational preferences of the subunits that make up the sequence of the biopolymer and by the interactions that are formed in the folded state in aqueous solution. Because of the centrality of these processes to life, quantifying conformational propensities and interaction strengths is vitally important to understanding biology. In this Account, we describe our use of peptide model systems that fold cooperatively yet are small enough to be chemically synthesized to measure such quantities. The necessary measurements are made by perturbing an interaction or conformation of interest by mutation and measuring the difference between the folding free energies of the wild type (in which the interaction or conformation is undisturbed) and the mutant model peptides (in which the interaction has been eliminated or the conformational propensities modified). With the proper controls and provided that the peptide model system in question folds via a two-state process, these folding free energy differences can be accurate measures of interaction strengths or conformational propensities. This method has the advantage of having high sensitivity and high dynamic range because the energies of interest are coupled to folding free energies, which can be measured with precisions on the order of a few tenths of a kilocalorie by well-established biophysical methods, like chaotrope or thermal denaturation studies monitored by fluorescence or circular dichroism. In addition, because the model peptides can be chemically synthesized, the full arsenal of natural and unnatural amino acids can be used to tune perturbations to be as drastic or subtle as desired. This feature is particularly noteworthy because it enables the use of analytical tools developed for physical organic chemistry, especially linear free energy relationships, to decompose interaction energies into their component parts to obtain a deeper understanding of the forces that drive interactions in biopolymers. We have used this approach, primarily with the WW domain derived from the human Pin1 protein as our model system, to assess hydrogen bond strengths (especially those formed by backbone amides), the dependence of hydrogen bond strengths on the environment in which they form, β-turn propensities of both natural sequences and small molecule β-turn mimics, and the energetics of carbohydrate-protein interactions. In each case, the combination of synthetic accessibility, the ease of measuring folding energies, and the robustness of the structure of the Pin1 WW domain to mutation enabled us to obtain incisive measurements of quantities that have been challenging to measure by other methods.

Determining the folding and binding free energy of DNA-based nanodevices and nanoswitches using urea titration curves

DNA nanotechnology takes advantage of the predictability of DNA interactions to build complex DNA-based functional nanoscale structures. However, when DNA functional and responsive units that are based on non-canonical DNA interactions are employed it becomes quite challenging to predict, understand and control their thermodynamics. In response to this limitation, here we demonstrate the use of isothermal urea titration experiments to estimate the free energy involved in a set of DNA-based systems ranging from unimolecular DNA-based nanoswitches to more complex DNA folds (e.g. aptamers) and nanodevices. We propose here a set of fitting equations that allow to analyze the urea titration curves of these DNA responsive units based on Watson-Crick and non-canonical interactions (stem-loop, G-quadruplex, triplex structures) and to correctly estimate their relative folding and binding free energy values under different experimental conditions. The results described herein will pave the way toward the use of urea titration experiments in the field of DNA nanotechnology to achieve easier and more reliable thermodynamic characterization of DNA-based functional responsive units. More generally, our results will be of general utility to characterize other complex supramolecular systems based on different biopolymers.

Computational tools help improve protein stability but with a solubility tradeoff

Accurately predicting changes in protein stability upon amino acid substitution is a much sought after goal. Destabilizing mutations are often implicated in disease, whereas stabilizing mutations are of great value for industrial and therapeutic biotechnology. Increasing protein stability is an especially challenging task, with random substitution yielding stabilizing mutations in only ∼2% of cases. To overcome this bottleneck, computational tools that aim to predict the effect of mutations have been developed; however, achieving accuracy and consistency remains challenging. Here, we combined 11 freely available tools into a meta-predictor (meieringlab.uwaterloo.ca/stabilitypredict/). Validation against ∼600 experimental mutations indicated that our meta-predictor has improved performance over any of the individual tools. The meta-predictor was then used to recommend 10 mutations in a previously designed protein of moderate thermodynamic stability, ThreeFoil. Experimental characterization showed that four mutations increased protein stability and could be amplified through ThreeFoil's structural symmetry to yield several multiple mutants with >2-kcal/mol stabilization. By avoiding residues within functional ties, we could maintain ThreeFoil's glycan-binding capacity. Despite successfully achieving substantial stabilization, however, almost all mutations decreased protein solubility, the most common cause of protein design failure. Examination of the 600-mutation data set revealed that stabilizing mutations on the protein surface tend to increase hydrophobicity and that the individual tools favor this approach to gain stability. Thus, whereas currently available tools can increase protein stability and combining them into a meta-predictor yields enhanced reliability, improvements to the potentials/force fields underlying these tools are needed to avoid gaining protein stability at the cost of solubility.

Biological effects of the hypomagnetic field: An analytical review of experiments and theories

During interplanetary flights in the near future, a human organism will be exposed to prolonged periods of a hypomagnetic field that is 10,000 times weaker than that of Earth's. Attenuation of the geomagnetic field occurs in buildings with steel walls and in buildings with steel reinforcement. It cannot be ruled out also that a zero magnetic field might be interesting in biomedical studies and therapy. Further research in the area of hypomagnetic field effects, as shown in this article, is capable of shedding light on a fundamental problem in biophysics-the problem of primary magnetoreception. This review contains, currently, the most extensive bibliography on the biological effects of hypomagnetic field. This includes both a review of known experimental results and the putative mechanisms of magnetoreception and their explanatory power with respect to the hypomagnetic field effects. We show that the measured correlations of the HMF effect with HMF magnitude and inhomogeneity and type and duration of exposure are statistically absent. This suggests that there is no general biophysical MF target similar for different organisms. This also suggests that magnetoreception is not necessarily associated with evolutionary developed specific magnetoreceptors in migrating animals and magnetotactic bacteria. Independently, there is nonspecific magnetoreception that is common for all organisms, manifests itself in very different biological observables as mostly random reactions, and is a result of MF interaction with magnetic moments at a physical level-moments that are present everywhere in macromolecules and proteins and can sometimes transfer the magnetic signal at the level of downstream biochemical events. The corresponding universal mechanism of magnetoreception that has been given further theoretical analysis allows one to determine the parameters of magnetic moments involved in magnetoreception-their gyromagnetic ratio and thermal relaxation time-and so to better understand the nature of MF targets in organisms.

Protein folding by NMR

Protein folding is a highly complex process proceeding through a number of disordered and partially folded nonnative states with various degrees of structural organization. These transiently and sparsely populated species on the protein folding energy landscape play crucial roles in driving folding toward the native conformation, yet some of these nonnative states may also serve as precursors for protein misfolding and aggregation associated with a range of devastating diseases, including neuro-degeneration, diabetes and cancer. Therefore, in vivo protein folding is often reshaped co- and post-translationally through interactions with the ribosome, molecular chaperones and/or other cellular components. Owing to developments in instrumentation and methodology, solution NMR spectroscopy has emerged as the central experimental approach for the detailed characterization of the complex protein folding processes in vitro and in vivo. NMR relaxation dispersion and saturation transfer methods provide the means for a detailed characterization of protein folding kinetics and thermodynamics under native-like conditions, as well as modeling high-resolution structures of weakly populated short-lived conformational states on the protein folding energy landscape. Continuing development of isotope labeling strategies and NMR methods to probe high molecular weight protein assemblies, along with advances of in-cell NMR, have recently allowed protein folding to be studied in the context of ribosome-nascent chain complexes and molecular chaperones, and even inside living cells. Here we review solution NMR approaches to investigate the protein folding energy landscape, and discuss selected applications of NMR methodology to studying protein folding in vitro and in vivo. Together, these examples highlight a vast potential of solution NMR in providing atomistic insights into molecular mechanisms of protein folding and homeostasis in health and disease.

On the polymer physics origins of protein folding thermodynamics

A remarkable feature of the spontaneous folding of many small proteins is the striking similarity in the thermodynamics of the folding process. This process is characterized by simple two-state thermodynamics with large and compensating changes in entropy and enthalpy and a funnel-like free energy landscape with a free-energy barrier that varies linearly with temperature. One might attribute the commonality of this two-state folding behavior to features particular to these proteins (e.g., chain length, hydrophobic/hydrophilic balance, attributes of the native state) or one might suspect that this similarity in behavior has a more general polymer-physics origin. Here we show that this behavior is also typical for flexible homopolymer chains with sufficiently short range interactions. Two-state behavior arises from the presence of a low entropy ground (folded) state separated from a set of high entropy disordered (unfolded) states by a free energy barrier. This homopolymer model exhibits a funneled free energy landscape that reveals a complex underlying dynamics involving competition between folding and non-folding pathways. Despite the presence of multiple pathways, this simple physics model gives the robust result of two-state thermodynamics for both the cases of folding from a basin of expanded coil states and from a basin of compact globule states.

Evidence for the principle of minimal frustration in the evolution of protein folding landscapes

Theoretical and experimental studies have firmly established that protein folding can be described by a funneled energy landscape. This funneled energy landscape is the result of foldable protein sequences evolving following the principle of minimal frustration, which allows proteins to rapidly fold to their native biologically functional conformations. For a protein family with a given functional fold, the principle of minimal frustration suggests that, independent of sequence, all proteins within this family should fold with similar rates. However, depending on the optimal living temperature of the organism, proteins also need to modulate their thermodynamic stability. Consequently, the difference in thermodynamic stability should be primarily caused by differences in the unfolding rates. To test this hypothesis experimentally, we performed comprehensive thermodynamic and kinetic analyses of 15 different proteins from the thioredoxin family. Eight of these thioredoxins were extant proteins from psychrophilic, mesophilic, or thermophilic organisms. The other seven protein sequences were obtained using ancestral sequence reconstruction and can be dated back over 4 billion years. We found that all studied proteins fold with very similar rates but unfold with rates that differ up to three orders of magnitude. The unfolding rates correlate well with the thermodynamic stability of the proteins. Moreover, proteins that unfold slower are more resistant to proteolysis. These results provide direct experimental support to the principle of minimal frustration hypothesis.

Control of human VDAC-2 scaffold dynamics by interfacial tryptophans is position specific

Membrane proteins employ specific distribution patterns of amino acids in their tertiary structure for adaptation to their unique bilayer environment. The solvent-bilayer interface, in particular, displays the characteristic ‘aromatic belt’ that defines the transmembrane region of the protein, and satisfies the amphipathic interfacial environment. Tryptophan—the key residue of this aromatic belt—is known to influence the folding efficiency and stability of a large number of well-studied α-helical and β-barrel membrane proteins. Here, we have used functional and biophysical techniques coupled with simulations, to decipher the contribution of strategically placed four intrinsic tryptophans of the human outer mitochondrial membrane protein, voltage-dependent anion channel isoform-2 (VDAC-2). We show that tryptophans help in maintaining the structural and functional integrity of folded hVDAC-2 barrel in micellar environments. The voltage gating characteristics of hVDAC-2 are affected upon mutation of tryptophans at positions 75, 86 and 221. We observe that Trp-160 and Trp-221 play a crucial role in the folding pathway of the barrel, and once folded, Trp-221 helps stabilize the folded protein in concert with Trp-75 and Trp-160. We further demonstrate that substituting Trp-86 with phenylalanine leads to the formation of stable barrel. We find that the region comprising strand β4 (Trp-86) and β10-14 (Trp-160 and Trp-221) display slower and faster folding kinetics, respectively, providing insight into a possible directional folding of hVDAC-2 from the C-terminus to N-terminus. Our results show that residue selection in a protein during evolution is a balancing compromise between optimum stability, function, and regulating protein turnover inside the cell.

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Aromatic belt of membrane proteins has key stabilization role.

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Human voltage-dependent anion channel isoform-2 (hVDAC-2) has four interfacial indoles.

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Tryptophans act in concert to drive folding and stabilization of the barrel.

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The 86th position shows preference for phenylalanine due to its buried environment.

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Strands β10–14 promote barrel folding and stabilize hVDAC-2.

The Kinetic Stability of a Full-Length Antibody Light Chain Dimer Determines whether Endoproteolysis Can Release Amyloidogenic Variable Domains

Light chain (LC) amyloidosis (AL amyloidosis) appears to be caused by the misfolding, or misfolding and aggregation of an antibody LC or fragment thereof and is fatal if untreated. LCs are secreted from clonally expanded plasma cells, generally as disulfide-linked dimers, with each monomer comprising one constant and one variable domain. The energetic contribution of each domain and the role of endoproteolysis in AL amyloidosis remain unclear. To investigate why only some LCs form amyloid and cause organ toxicity, we measured the aggregation propensity and kinetic stability of LC dimers and their associated variable domains from AL amyloidosis patients and non-patients. All the variable domains studied readily form amyloid fibrils, whereas none of the full-length LC dimers, even those from AL amyloidosis patients, are amyloidogenic. Kinetic stability-that is, the free energy difference between the native state and the unfolding transition state-dictates the LC's unfolding rate. Full-length LC dimers derived from AL amyloidosis patients unfold more rapidly than other full-length LC dimers and can be readily cleaved into their component domains by proteases, whereas non-amyloidogenic LC dimers are more kinetically stable and resistant to endoproteolysis. Our data suggest that amyloidogenic LC dimers are kinetically unstable (unfold faster) and are thus susceptible to endoproteolysis that results in the release amyloidogenic LC fragments, whereas other LCs are not as amenable to unfolding and endoproteolysis and are therefore aggregation resistant. Pharmacologic kinetic stabilization of the full-length LC dimer could be a useful strategy to treat AL amyloidosis.

A Soluble, Folded Protein without Charged Amino Acid Residues

Charges are considered an integral part of protein structure and function, enhancing solubility and providing specificity in molecular interactions. We wished to investigate whether charged amino acids are indeed required for protein biogenesis and whether a protein completely free of titratable side chains can maintain solubility, stability, and function. As a model, we used a cellulose-binding domain from Cellulomonas fimi, which, among proteins of more than 100 amino acids, presently is the least charged in the Protein Data Bank, with a total of only four titratable residues. We find that the protein shows a surprising resilience toward extremes of pH, demonstrating stability and function (cellulose binding) in the pH range from 2 to 11. To ask whether the four charged residues present were required for these properties of this protein, we altered them to nontitratable ones. Remarkably, this chargeless protein is produced reasonably well in Escherichia coli, retains its stable three-dimensional structure, and is still capable of strong cellulose binding. To further deprive this protein of charges, we removed the N-terminal charge by acetylation and studied the protein at pH 2, where the C-terminus is effectively protonated. Under these conditions, the protein retains its function and proved to be both soluble and have a reversible folding-unfolding transition. To the best of our knowledge, this is the first time a soluble, functional protein with no titratable side chains has been produced.

Development and Application of a High Throughput Protein Unfolding Kinetic Assay

The kinetics of folding and unfolding underlie protein stability and quantification of these rates provides important insights into the folding process. Here, we present a simple high throughput protein unfolding kinetic assay using a plate reader that is applicable to the studies of the majority of 2-state folding proteins. We validate the assay by measuring kinetic unfolding data for the SH3 (Src Homology 3) domain from Actin Binding Protein 1 (AbpSH3) and its stabilized mutants. The results of our approach are in excellent agreement with published values. We further combine our kinetic assay with a plate reader equilibrium assay, to obtain indirect estimates of folding rates and use these approaches to characterize an AbpSH3-peptide hybrid. Our high throughput protein unfolding kinetic assays allow accurate screening of libraries of mutants by providing both kinetic and equilibrium measurements and provide a means for in-depth ϕ-value analyses.

Prediction of protein folding rates from simplified secondary structure alphabet

Protein folding is a very complicated and highly cooperative dynamic process. However, the folding kinetics is likely to depend more on a few key structural features. Here we find that secondary structures can determine folding rates of only large, multi-state folding proteins and fails to predict those for small, two-state proteins. The importance of secondary structures for protein folding is ordered as: extended β strand > α helix > bend > turn > undefined secondary structure>310 helix > isolated β strand > π helix. Only the first three secondary structures, extended β strand, α helix and bend, can achieve a good correlation with folding rates. This suggests that the rate-limiting step of protein folding would depend upon the formation of regular secondary structures and the buckling of chain. The reduced secondary structure alphabet provides a simplified description for the machine learning applications in protein design.